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论文类型：期刊论文

发表时间：2011-01-01

发表刊物：NEURAL NETWORK WORLD

收录刊物：SCIE、EI、Scopus

卷号：21

期号：5

页面范围：461-472

ISSN号：1210-0552

关键字：Intuitionistic fuzzy sets; intuitionistic fuzzy Hopfield neural network; limit cycle; stable point; Lyapunov stability

摘要：Intuitionistic fuzzy sets (IFSs) are generalization of fuzzy sets by adding an additional attribute parameter called non-membership degree. In this paper, a max-min intuitionistic fuzzy Hopfield neural network (IFHNN) is proposed by combining IFSs with Hopfield neural networks. The stability of IFHNN is investigated. It is shown that for any given weight matrix and any given initial intuitionistic fuzzy pattern, the iteration process of IFHNN converges to a limit cycle. Furthermore, under suitable extra conditions, it converges to a stable point within finite iterations. Finally, a kind of Lyapunov stability of the stable points of IFHNN is proved, which means that if the initial state of the network is close enough to a stable point, then the network states will remain in a small neighborhood of the stable point. These stability results indicate the convergence of memory process of IFHNN. A numerical example is also provided to show the effectiveness of the Lyapunov stability of IFHNN